ngrok AI Gateway provides one hosted gateway for every model: public providers, custom endpoints, and the models you run yourself. Use one key and one URL to route across OpenAI, Anthropic, and self-hosted models with observability, access control, and fallbacks built in. Your private models connect through ngrok’s network, so they sit beside hosted providers without being exposed to the public internet.
I'm Niji, a product manager at ngrok. Today we're launching ngrok.ai, ngrok's AI Gateway.
For years, ngrok has helped developers connect their applications and services in minutes instead of days.
As I started building with AI, I ran into similar infrastructure problems at the application layer.
An application might start with OpenAI, then Claude for another use case. As newer, faster, or more affordable models became available, I would create more accounts and update my code just to try them. Eventually, more specialized needs would lead me to run fine-tuned or task-specific models on my laptop, private GPUs, or internal cloud infrastructure.
Before long, I was managing multiple gateways and SDKs, sharing provider keys across configuration files and vaults, checking usage in several dashboards, maintaining complicated fallback logic, and accidentally exposing models that were supposed to remain private.
If any of this sounds familiar, it is why we built ngrok.ai. It gives you one hosted gateway for managing models across providers, private infrastructure, and your own hardware.
One URL for every model
Getting started is simple. Point your SDK at https://gateway.ngrok.ai with your ngrok.ai access key, and begin routing requests to public providers, custom endpoints, and models you run yourself.
It works with all popular SDKs like OpenAI, Anthropic, and Vercel AI, so you can easily swap models and providers without rebuilding your entire application.
Aside from being a hosted AI Gateway, we enable you to:
Connect self-hosted models privately Route to a model running on your laptop, local GPU, or private network without complex networking, opening inbound ports or dealing with IPs.
Build fallbacks into the gateway Define a list of models and when a model or key fails, we will make another attempt or route the request to a healthy alternative.
Use credits to make requests Leverage ngrok.ai to make requests against OpenAI, Anthropic, z.ai and more without having to create your own accounts with each provider.
Use your existing provider keys Don't want to use our accounts? No worries, you can bring your own OpenAI, Anthropic, or custom provider keys that you already.
Control access by application or developer Create separate access keys and decide which providers and models each one is allowed to call, and which keys each model should use, whether ours or yours.
See usage across your entire model stack Track tokens, latency, errors, models, providers, and estimated cost in one place instead of piecing together several provider dashboards.
Manage everything through the dashboard or API Set up gateways, keys, providers, access rules, and routing from your own tooling using our API or directly in the ngrok.ai dashboard.
Who we're building this for
ngrok.ai is for developers and platform teams that want the freedom to use the right model for each job without worrying about how to scale and maintain an ai gateway themselves and or taking on another infrastructure project every time their model strategy changes.
We're especially interested in hearing:
How are you routing between models today?
Are you running any models on your own infrastructure?
Which gateway features would make your AI stack easier to manage?
We'll be here throughout the launch to answer questions and hear what you think. Thanks for checking it out.
About ngrok AI Gateway on Product Hunt
“One private gateway for every AI model”
ngrok AI Gateway launched on Product Hunt on August 5th, 2026 and earned 271 upvotes and 51 comments, placing #4 on the daily leaderboard. ngrok AI Gateway provides one hosted gateway for every model: public providers, custom endpoints, and the models you run yourself. Use one key and one URL to route across OpenAI, Anthropic, and self-hosted models with observability, access control, and fallbacks built in. Your private models connect through ngrok’s network, so they sit beside hosted providers without being exposed to the public internet.
On the analytics side, ngrok AI Gateway competes within Software Engineering, Developer Tools and Artificial Intelligence — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how ngrok AI Gateway performed against the three products that launched closest to it on the same day.
Who hunted ngrok AI Gateway?
ngrok AI Gateway was hunted by fmerian. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of ngrok AI Gateway including community comment highlights and product details, visit the product overview.
fmerian
Hey Product Hunt 👋
I'm Niji, a product manager at ngrok. Today we're launching ngrok.ai, ngrok's AI Gateway.
For years, ngrok has helped developers connect their applications and services in minutes instead of days.
As I started building with AI, I ran into similar infrastructure problems at the application layer.
An application might start with OpenAI, then Claude for another use case. As newer, faster, or more affordable models became available, I would create more accounts and update my code just to try them. Eventually, more specialized needs would lead me to run fine-tuned or task-specific models on my laptop, private GPUs, or internal cloud infrastructure.
Before long, I was managing multiple gateways and SDKs, sharing provider keys across configuration files and vaults, checking usage in several dashboards, maintaining complicated fallback logic, and accidentally exposing models that were supposed to remain private.
If any of this sounds familiar, it is why we built ngrok.ai. It gives you one hosted gateway for managing models across providers, private infrastructure, and your own hardware.
One URL for every model
Getting started is simple. Point your SDK at https://gateway.ngrok.ai with your ngrok.ai access key, and begin routing requests to public providers, custom endpoints, and models you run yourself.
It works with all popular SDKs like OpenAI, Anthropic, and Vercel AI, so you can easily swap models and providers without rebuilding your entire application.
Aside from being a hosted AI Gateway, we enable you to:
Connect self-hosted models privately
Route to a model running on your laptop, local GPU, or private network without complex networking, opening inbound ports or dealing with IPs.
Build fallbacks into the gateway
Define a list of models and when a model or key fails, we will make another attempt or route the request to a healthy alternative.
Use credits to make requests
Leverage ngrok.ai to make requests against OpenAI, Anthropic, z.ai and more without having to create your own accounts with each provider.
Use your existing provider keys
Don't want to use our accounts? No worries, you can bring your own OpenAI, Anthropic, or custom provider keys that you already.
Control access by application or developer
Create separate access keys and decide which providers and models each one is allowed to call, and which keys each model should use, whether ours or yours.
See usage across your entire model stack
Track tokens, latency, errors, models, providers, and estimated cost in one place instead of piecing together several provider dashboards.
Manage everything through the dashboard or API
Set up gateways, keys, providers, access rules, and routing from your own tooling using our API or directly in the ngrok.ai dashboard.
Who we're building this for
ngrok.ai is for developers and platform teams that want the freedom to use the right model for each job without worrying about how to scale and maintain an ai gateway themselves and or taking on another infrastructure project every time their model strategy changes.
We're especially interested in hearing:
How are you routing between models today?
Are you running any models on your own infrastructure?
Which gateway features would make your AI stack easier to manage?
We'll be here throughout the launch to answer questions and hear what you think. Thanks for checking it out.